Therapy Contamination as a Measure of Therapist Treatment Adherence in a Trial of Cognitive Behaviour Therapy versus Befriending for Psychosis
Bibliographic record
Abstract
BACKGROUND: High quality randomized controlled trials (RCT) of psychotherapeutic interventions should ensure that the therapy being tested is what is actually delivered. However, contamination of one therapy into the other, a critical component of treatment adherence, is seldom measured in psychotherapy trials of psychosis. AIMS: The aim of the study was to determine whether a purpose-designed measure, the ACE Treatment Integrity Measure (ATIM) could detect therapy contaminations within a controlled trial of cognitive behavioural therapy (CBT) versus Befriending for first-episode psychosis and to compare the ATIM to a more traditional adherence measure, the Cognitive Therapy Scale (CTS). METHOD: Therapy sessions were audio-recorded and at least one therapy session from 53 of the 62 participants in the RCT was rated by an independent rater using the CTS and ATIM. RESULTS: Ninety-nine therapy sessions were rated. All Befriending sessions and all but three CBT sessions were correctly identified. The ATIM showed that 29 of the 99 (29%) sessions were contaminated by techniques from the other therapy. Within the CBT sessions, 19 of the 51 sessions (37%) were contaminated by one or more Befriending techniques. Of the Befriending sessions, 10 of 48 (21%) were contaminated by ACE techniques. The mean CTS score was higher in the CBT than the Befriending group. CONCLUSIONS: The ATIM was able to detect contaminations and revealed more meaningful, fine-grained analysis of what therapy techniques were being delivered and what contaminations occurred. The study highlights the benefit of employing purpose-designed measures that include contamination when assessing treatment adherence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".